code: def scatter_mul(ref, indices, updates, use_locking=False, name=None):
      # pylint: disable=line-too-long
      r"""Multiplies sparse updates into a variable reference.
  
      This operation computes
  
      ```python
          # Scalar indices
          ref[indices, ...] *= updates[...]
  
          # Vector indices (for each i)
          ref[indices[i], ...] *= updates[i, ...]
  
          # High rank indices (for each i, ..., j)
          ref[indices[i, ..., j], ...] *= updates[i, ..., j, ...]
      ```
  
      This operation outputs `ref` after the update is done.
      This makes it easier to chain operations that need to use the reset value.
  
      Duplicate entries are handled correctly: if multiple `indices` reference
      the same location, their contributions multiply.
  
      Requires `updates.shape = indices.shape + ref.shape[1:]` or `updates.shape =
      []`.
  
      Args:
        ref: A mutable `Tensor`. Must be one of the following types: `float32`,
          `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`,
          `qint8`, `quint8`, `qint32`, `bfloat16`, `uint16`, `complex128`, `half`,
          `uint32`, `uint64`. Should be from a `Variable` node.
        indices: A `Tensor`. Must be one of the following types: `int32`, `int64`. A
          tensor of indices into the first dimension of `ref`.
        updates: A `Tensor`. Must have the same type as `ref`. A tensor of updated
          values to multiply to `ref`.
        use_locking: An optional `bool`. Defaults to `False`. If True, the operation
          will be protected by a lock; otherwise the behavior is undefined, but may
          exhibit less contention.
        name: A name for the operation (optional).
  
      Returns:
        A mutable `Tensor`. Has the same type as `ref`.
      """
      if ref.dtype._is_ref_dtype:
          return gen_state_ops.scatter_mul(
              ref, indices, updates, use_locking=use_locking, name=name
          )
      return ref._lazy_read(
          gen_resource_variable_ops.resource_scatter_mul(  # pylint: disable=protected-access
              ref.handle,
              indices,
              ops.convert_to_tensor(updates, ref.dtype),
              name=name,
          )
      )
  
imports: from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import gen_resource_variable_ops
  from tensorflow.python.ops import gen_state_ops
  from tensorflow.python.ops import state_grad
  from tensorflow.python.ops.gen_state_ops import *
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.deprecation import deprecated
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 15 for calling a global function with example usage: scatter_mul(ref, indices, updates, use_locking, name) and returns: ref, gen_state_ops